data-science-ipython-notebooks/matplotlib/matplotlib.ipynb
2015-04-10 11:38:25 -04:00

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{
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"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# matplotlib"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* Setting Global Parameters\n",
"* Bar Plots, Histograms, subplot2grid\n",
"* Normalized Plots\n",
"* Scatter Plots, subplots\n",
"* Kernel Density Estimation Plots\n",
"* Basic Plots\n",
"* Histograms\n",
"* Two Histograms on the Same Plot\n",
"* Scatter Plots"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"import numpy as np\n",
"import pylab as plt\n",
"import seaborn\n",
"\n",
"%matplotlib inline\n",
"\n",
"seaborn.set()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Prepare data to plot:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df_train = pd.read_csv('../data/titanic/train.csv')\n",
"\n",
"def clean_data(df):\n",
" \n",
" # Get the unique values of Sex\n",
" sexes = sort(df['Sex'].unique())\n",
" \n",
" # Generate a mapping of Sex from a string to a number representation \n",
" genders_mapping = dict(zip(sexes, range(0, len(sexes) + 1)))\n",
"\n",
" # Transform Sex from a string to a number representation\n",
" df['Sex_Val'] = df['Sex'].map(genders_mapping).astype(int)\n",
" \n",
" # Get the unique values of Embarked\n",
" embarked_locs = sort(df['Embarked'].unique())\n",
"\n",
" # Generate a mapping of Embarked from a string to a number representation \n",
" embarked_locs_mapping = dict(zip(embarked_locs, \n",
" range(0, len(embarked_locs) + 1)))\n",
" \n",
" # Transform Embarked from a string to dummy variables\n",
" df = pd.concat([df, pd.get_dummies(df['Embarked'], prefix='Embarked_Val')], axis=1)\n",
" \n",
" # Fill in missing values of Embarked\n",
" # Since the vast majority of passengers embarked in 'S': 3, \n",
" # we assign the missing values in Embarked to 'S':\n",
" if len(df[df['Embarked'].isnull()] > 0):\n",
" df.replace({'Embarked_Val' : \n",
" { embarked_locs_mapping[nan] : embarked_locs_mapping['S'] \n",
" }\n",
" }, \n",
" inplace=True)\n",
" \n",
" # Fill in missing values of Fare with the average Fare\n",
" if len(df[df['Fare'].isnull()] > 0):\n",
" avg_fare = df['Fare'].mean()\n",
" df.replace({ None: avg_fare }, inplace=True)\n",
" \n",
" # To keep Age in tact, make a copy of it called AgeFill \n",
" # that we will use to fill in the missing ages:\n",
" df['AgeFill'] = df['Age']\n",
"\n",
" # Determine the Age typical for each passenger class by Sex_Val. \n",
" # We'll use the median instead of the mean because the Age \n",
" # histogram seems to be right skewed.\n",
" df['AgeFill'] = df['AgeFill'] \\\n",
" .groupby([df['Sex_Val'], df['Pclass']]) \\\n",
" .apply(lambda x: x.fillna(x.median()))\n",
" \n",
" # Define a new feature FamilySize that is the sum of \n",
" # Parch (number of parents or children on board) and \n",
" # SibSp (number of siblings or spouses):\n",
" df['FamilySize'] = df['SibSp'] + df['Parch']\n",
" \n",
" return df\n",
"\n",
"df_train = clean_data(df_train)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Setting Global Parameters"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Set the global default size of matplotlib figures\n",
"plt.rc('figure', figsize=(10, 5))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Bar Plots, Histograms, subplot2grid"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Size of matplotlib figures that contain subplots\n",
"figsize_with_subplots = (10, 10)\n",
"\n",
"# Set up a grid of plots\n",
"fig = plt.figure(figsize=figsize_with_subplots) \n",
"fig_dims = (3, 2)\n",
"\n",
"# Plot death and survival counts\n",
"plt.subplot2grid(fig_dims, (0, 0))\n",
"df_train['Survived'].value_counts().plot(kind='bar', \n",
" title='Death and Survival Counts',\n",
" color='r',\n",
" align='center')\n",
"\n",
"# Plot Pclass counts\n",
"plt.subplot2grid(fig_dims, (0, 1))\n",
"df_train['Pclass'].value_counts().plot(kind='bar', \n",
" title='Passenger Class Counts')\n",
"\n",
"# Plot Sex counts\n",
"plt.subplot2grid(fig_dims, (1, 0))\n",
"df_train['Sex'].value_counts().plot(kind='bar', \n",
" title='Gender Counts')\n",
"plt.xticks(rotation=0)\n",
"\n",
"# Plot Embarked counts\n",
"plt.subplot2grid(fig_dims, (1, 1))\n",
"df_train['Embarked'].value_counts().plot(kind='bar', \n",
" title='Ports of Embarkation Counts')\n",
"\n",
"# Plot the Age histogram\n",
"plt.subplot2grid(fig_dims, (2, 0))\n",
"df_train['Age'].hist()\n",
"plt.title('Age Histogram')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": [
"<matplotlib.text.Text at 0x10bf0fed0>"
]
},
{
"metadata": {},
"output_type": "display_data",
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RnqlbgNsAMvPWiPgDsFfD6/OBu4A1QF/D9j5gcKxCFy6cy4wZ07e6wq0wODivI8edLBYt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\nkiRV8P8AUrk88f84hHIAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10bbc2b50>"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Get the unique values of Embarked and its maximum\n",
"family_sizes = sort(df_train['FamilySize'].unique())\n",
"family_size_max = max(family_sizes)\n",
"\n",
"df1 = df_train[df_train['Survived'] == 0]['FamilySize']\n",
"df2 = df_train[df_train['Survived'] == 1]['FamilySize']\n",
"plt.hist([df1, df2], \n",
" bins=family_size_max + 1, \n",
" range=(0, family_size_max), \n",
" stacked=True)\n",
"plt.legend(('Died', 'Survived'), loc='best')\n",
"plt.title('Survivors by Family Size')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
"<matplotlib.text.Text at 0x10c679150>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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1FZxS7Sq0I4bKz1d7ezuLFy/auQXtoGOPPc7hzho1XH6+cvdgvQeoj4hjUkp/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\n",
"text": [
"<matplotlib.figure.Figure at 0x10bbbb090>"
]
}
],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Normalized Plots"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pclass_xt = pd.crosstab(df_train['Pclass'], df_train['Survived'])\n",
"\n",
"# Normalize the cross tab to sum to 1:\n",
"pclass_xt_pct = pclass_xt.div(pclass_xt.sum(1).astype(float), axis=0)\n",
"\n",
"pclass_xt_pct.plot(kind='bar', \n",
" stacked=True, \n",
" title='Survival Rate by Passenger Classes')\n",
"plt.xlabel('Passenger Class')\n",
"plt.ylabel('Survival Rate')\n",
"\n",
"# Plot survival rate by Sex\n",
"females_df = df_train[df_train['Sex'] == 'female']\n",
"females_xt = pd.crosstab(females_df['Pclass'], df_train['Survived'])\n",
"females_xt_pct = females_xt.div(females_xt.sum(1).astype(float), axis=0)\n",
"females_xt_pct.plot(kind='bar', \n",
" stacked=True, \n",
" title='Female Survival Rate by Passenger Class')\n",
"plt.xlabel('Passenger Class')\n",
"plt.ylabel('Survival Rate')\n",
"\n",
"# Plot survival rate by Pclass\n",
"males_df = df_train[df_train['Sex'] == 'male']\n",
"males_xt = pd.crosstab(males_df['Pclass'], df_train['Survived'])\n",
"males_xt_pct = males_xt.div(males_xt.sum(1).astype(float), axis=0)\n",
"males_xt_pct.plot(kind='bar', \n",
" stacked=True, \n",
" title='Male Survival Rate by Passenger Class')\n",
"plt.xlabel('Passenger Class')\n",
"plt.ylabel('Survival Rate')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": [
"<matplotlib.text.Text at 0x10ca22f50>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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VMnxJkiRVyPAlSZJUIcOXJElShQxfkiRJFTJ8SZIkVcjwJUmSVCHDlyRJUoUM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\nJEmSKvT/AdrOw+EZX3rtAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c8a9f10>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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JkqQKGb4kSZIqZPiSJEmqkOFLkiSpQoYvSZKkChm+JEmSKmT4kiRJqpDhS5Ik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\nn6BBhs62AAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c928450>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10c9c2690>"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Scatter Plots, subplots"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Set up a grid of plots\n",
"fig, axes = plt.subplots(2, 1, figsize=figsize_with_subplots)\n",
"\n",
"# Histogram of AgeFill segmented by Survived\n",
"df1 = df_train[df_train['Survived'] == 0]['Age']\n",
"df2 = df_train[df_train['Survived'] == 1]['Age']\n",
"max_age = max(df_train['AgeFill'])\n",
"\n",
"axes[1].hist([df1, df2], \n",
" bins=max_age / 10, \n",
" range=(1, max_age), \n",
" stacked=True)\n",
"axes[1].legend(('Died', 'Survived'), loc='best')\n",
"axes[1].set_title('Survivors by Age Groups Histogram')\n",
"axes[1].set_xlabel('Age')\n",
"axes[1].set_ylabel('Count')\n",
"\n",
"# Scatter plot Survived and AgeFill\n",
"axes[0].scatter(df_train['Survived'], df_train['AgeFill'])\n",
"axes[0].set_title('Survivors by Age Plot')\n",
"axes[0].set_xlabel('Survived')\n",
"axes[0].set_ylabel('Age')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": [
"<matplotlib.text.Text at 0x10bfbe890>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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Xqn29qhlJkoqrvn4R2dSY3fPbrXlMlVDxAi0iFkXE6ymlJrJi7ewuebwODKt0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\nTJ6DJkmSVBgLmiRJUmEsaJIkSYWxoEmSJBXGgiZ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"text": [
"<matplotlib.figure.Figure at 0x10c8a98d0>"
]
}
],
"prompt_number": 7
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Kernel Density Estimation Plots"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Get the unique values of Pclass:\n",
"passenger_classes = sort(df_train['Pclass'].unique())\n",
"\n",
"for pclass in passenger_classes:\n",
" df_train.AgeFill[df_train.Pclass == pclass].plot(kind='kde')\n",
"plt.title('Age Density Plot by Passenger Class')\n",
"plt.xlabel('Age')\n",
"plt.legend(('1st Class', '2nd Class', '3rd Class'), loc='best')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 8,
"text": [
"<matplotlib.legend.Legend at 0x10d0a7750>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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2FBUR6S0FbCJJrrm8EldKCu7MzISU780NB2xa2kNEpPcUsIkkueaKCnz58V+D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\nIrkAAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10bdc1ed0>"
]
}
],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Basic Plots"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = np.linspace(0, 2, 10)\n",
"\n",
"plt.plot(x, x, 'o-', label='linear')\n",
"plt.plot(x, x ** 2, 'x-', label='quadratic')\n",
"\n",
"plt.legend(loc='best')\n",
"plt.title('Linear vs Quadratic progression')\n",
"plt.xlabel('Input')\n",
"plt.ylabel('Output');\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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gWnxcIqnFUYvGmFca2fZPb8oRERGJDL/jZ/GWd7nviz9RVFnMGTlTuXH8TxTK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\nRK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c9ff410>"
]
}
],
"prompt_number": 9
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Histograms"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Gaussian, mean 1, stddev .5, 1000 elements\n",
"samples = np.random.normal(loc=1.0, scale=0.5, size=1000)\n",
"print(samples.shape)\n",
"print(samples.dtype)\n",
"print(samples[:30])\n",
"plt.hist(samples, bins=50);\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(1000,)\n",
"float64\n",
"[ 0.78414546 0.7624507 0.79832022 1.43772119 0.6277384 0.95119108\n",
" 0.86033247 2.05204185 1.34378449 0.51229619 2.08940893 1.96080879\n",
" 0.90780563 0.82401283 0.63668015 1.50731702 1.52091633 0.59678776\n",
" 0.5543333 0.67782493 0.64534513 0.87408671 0.99390343 1.81493002\n",
" 0.46069816 1.31869943 1.26709913 1.96472827 0.97586513 0.96092536]\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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dAlWt9f8l+cHNr/8wyZ3DKwkAYLL4YE8AgEY7mUMFAM3WrlzOmTOne7br0gZ2m0AFwK54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\nQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10d0b2d90>"
]
}
],
"prompt_number": 10
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Two Histograms on the Same Plot"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"samples_1 = np.random.normal(loc=1, scale=.5, size=10000)\n",
"samples_2 = np.random.standard_t(df=10, size=10000)\n",
"bins = np.linspace(-3, 3, 50)\n",
"\n",
"# Set an alpha and use the same bins since we are plotting two hists\n",
"plt.hist(samples_1, bins=bins, alpha=0.5, label='samples 1')\n",
"plt.hist(samples_2, bins=bins, alpha=0.5, label='samples 2')\n",
"plt.legend(loc='upper left');\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10d500610>"
]
}
],
"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Scatter Plots"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.scatter(samples_1, samples_2, alpha=0.1);\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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6twnib/DPnsVDhI5TYW+vS7lcXQ6p9djaimeQtdsumnbS8wNxXs7+vsdi8Zjp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"text": [
"<matplotlib.figure.Figure at 0x10d20c2d0>"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 12
}
],
"metadata": {}
}
]
}